Digital images and videos are represented by pixels that have color values. Typically, the color of each pixel is described by multiple component values. Each of the component values describes the extent to which a component contributes to the final color value. There are multiple methods by which sets of component values can be used to describe color values, and these methods are referred to as color spaces.
One way to represent color values is by using an RGB color space where each pixel is represented by individual values for red, green, blue color components that are added together to produce a particular color. Another way to represent color values is by separating luminance information and chrominance information, such as in a YUV color space (e.g. Y′CbCr). This type of color space is commonly used in image compression schemes for both still images and video, in part because it allows for chroma subsampling, which is a common technique for reducing the amount of data that is used to represent images and video.
Converting an image from one color space to another can result in a loss of color information. For example, some color space conversions cause a loss of spatial resolution as a result of downsampling, and some color space conversions cause range reduction (i.e., clipping) when some values in one color space are not representable in the other.
Chroma subsampling reduces the spatial resolution of color information while retaining the spatial resolution of brightness information. This reduction in color information is often not readily perceived by humans, because the human visual system is more sensitive to brightness than it is to color. There are certain types of images, however, in which chroma subsampling will introduce visually disturbing artifacts, such as in images containing text, striped patterns, checkerboard patterns, computer-rendered graphics, artificially generated smooth gradients, and in images with colorful details.